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list_objects

Read-onlyIdempotent

List every table and view this caller may read, with its kind and column count. Use it to see what exists before asking, or when select_schema did not return what you expected.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rolesNoThe caller's roles or groups, e.g. ['finance', 'payroll']. Objects and columns restricted to a role are visible only when it is listed here. Omitted = no roles.
principalNoWho is asking, as an identity string such as 'okta:jdoe'. Pass it whenever you know the user: visibility is decided for this identity. Omitted = anonymous, which sees only unrestricted objects.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior, so the safety profile is covered. The description adds that results are permission-filtered per caller identity, which is meaningful context beyond the annotations, but it says nothing about result size, truncation, or ordering for a tool that lists 'every' object.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, no filler, and the scope/payload statement is front-loaded ahead of the usage triggers. Every clause carries information an agent needs.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present, return-value explanation is not required, and the annotations carry the safety profile, so purpose plus usage plus visibility scoping is largely sufficient. The only gap is behavior on large catalogs (pagination or caps), which is minor for a metadata listing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% and both parameters (roles, principal) are fully documented in the schema, including defaults and visibility semantics. The description's phrase 'this caller may read' only alludes to that filtering rather than adding syntax or precedence detail, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('List every table and view'), plus the scope ('this caller may read') and the payload ('with its kind and column count'). This cleanly separates it from describe_object (detail on one object) and run_query (execution), so an agent can choose without opening a schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives two concrete trigger conditions ('to see what exists before asking' and 'when select_schema did not return what you expected') and names the sibling to fall back from. It stops short of stating when not to use it or how it relates to describe_object, so it is clear but not fully exhaustive.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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